An Effective Configuration of Ensemble Size and Horizontal Resolution for the NCEP GEFS

Two important questions are addressed in this paper using the Global Ensemble Forecast System （GEFS） from the National Centers for Environmental Prediction （NCEP）： （1） How many ensemble members are needed to better represent forecast uncertainties with limited computational resources？ （2） What is tile relative impact on forecast skill of increasing model resolution and ensemble size？ Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 members at the 500- hPa geopotential height. Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics, but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics. An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources. Two representative configurations of the GEFS the T126L28 model with 70 members and the T190L28 model with 20 members, which have equivalent computing costs--were compared. Results confirm that, for the NCEP GEFS, increasing the model resolution is more （less） beneficial than increasing the ensemble size for a short （long） forecast range.

20 TO 30-DAY AND 30 TO 60-DAY OSCILLATIONS IN ASSIMILATED GLOBAL DATASETS USING TRMM RAINFALL OBSERVATIONS

The influences of Tropical Rainfall Measuring Mission (TRMM) precipitation products on the structure and underlying physics of intraseasonal oscillation (ISO) are investigated with the U.S.National Aeronautics and Space Administration Goddard Earth Observing System model version 3 (GEOS-3) data assimilation system (DAS).The strong ISO phase in the 1998 summer is apparently located in the Asian monsoon region and the east equatorial Pacific region.The eastward propagation is a dominant feature for the tropical ISO at 20 to 30-day oscillation while the northeastward propagation is the salient ISO at 30 to 60-day oscillation over the 10°N to 25°N belt region.It appears that the Kelvin wave structure is for the tropical 20 to 30-day oscillation.The tropical 30 to 60-day oscillation has the characteristics of the Kelvin-Rossby wave.The impact of satellite-derived precipitation (and its associated latent heating) on the ISO intensity is limited in the GEOS-3 assimilation system.However,its impact on the ISO spatial structures is obvious.Overall,the results demonstrate a better eastward propagation and a northward propagation of ISO with the TRMM precipitation simulation,indicating that latent heating is very important in exciting the equatorial ISO.

Temperature-Profile/Lapse-Rate Feedback: A Misunderstood Feedback of the Climate System

This study shows that the heretofore assumed condition for no temperature-profile (TP)/lapse-rate feedback, for all altitudes z, or , in fact yields a negative feedback. The correct condition for no TP feedback is for all z, where Ts is the surface temperature. This condition translates into a uniform increase (decrease) in lapse rate with altitude for an increase (decrease) in Ts. The temperature changes caused by a change in solar irradiance and/or planetary albedo satisfy the condition for no TP feedback. The temperature changes caused by a change in greenhouse gas concentration do not satisfy the condition for no TP feedback and, instead, yield a positive feedback.

Diurnal Variability of Precipitation Depth Over the Tibetan Plateau and Its Surrounding Regions

The diurnal variability of precipitation depth over the Tibetan Plateau and its surrounding regions is investigated using nine years of Tropical Rainfall Measuring Mission （TRMM） precipitation radar （PR） measurements. The Tibetan Plateau, the plains area, and the East China Sea are selected as the focus regions in this study. The average precipitation depths （PD） are about 4.6 km, 5.8 km, and 5.6 km, while convective （stratiform） PDs are about 6.6 （4.5） km, 7.5 （5.7） km, and 6.0 （5.6） km over the plateau, the plains, and the ocean region, respectively. Results demonstrate a prominent PD diurnal cycle, and its diurnal phase is generally a few hours behind the surface precipitation. The spatial variation of the PD diurnal magnitude is weaker near the coastal areas than that of surface precipitation. The height of the PD diurnal peak is around 6 7 km for convective systems and 5-6 km for stratifrom systems. The dominant afternoon diurnal peak for convective PD and the flat diurnal peak for stratiform PD over the Tibetan Plateau indicate that solar diurnal forcing is the key mechanism of the PD diurnal cycle over land. In addition, the diurnal variation is obvious for shallow and deep convective systems, but not for shallow and deep stratiform systems.

Regional and Global Land Data Assimilation Systems: Innovations,Challenges, and Prospects

Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.

Quality Control and Evaluation of the Observed Daily Data in the North American Soil Moisture Database

The North American Soil Moisture Database (NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control (QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold (i.e., 0.6 m3 m-3) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network (SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this quality-controlled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when high-quality data become available in the future.

Satellite Data Assimilation of Upper-Level Sounding Channels in HWRF with Two Different Model Tops

The Advanced Microwave Sounding Unit-A（AMSU-A） onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites（EUMETSAT）Met Op-A, the hyperspectral Atmospheric Infrared Sounder（AIRS） onboard Aqua, the High resolution Infra Red Sounder（HIRS） onboard NOAA-19 and Met Op-A, and the Advanced Technology Microwave Sounder（ATMS） onboard Suomi National Polar-orbiting Partnership（NPP） satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting（HWRF） system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.

航空气象要素以及基于数值模式的低能见度和雾的预报

简述了对航空运输有危害的天气要素,包括航线要素和航站要素的业务预报。着重介绍了在美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)业务模式后处理中,能见度的两种诊断方法和雾的三种后处理再诊断方法。能见度计算的第一种方法是Stoelinga-Warner方法。该方法要求预报模式有四种水溶性物质的输出。通过这些水凝性物质计算消光系数来估算水平能见度。第二种方法是第一种方法的改进,包括增加了更多的水凝性物质,用相对湿度估算高湿度时或霾条件下的能见度,考虑了白天和夜间能见度的不同等。还讨论了以机场跑道为背景的跑道能见度的估计方法。雾的再诊断包括美国联合包裹速递服务公司(United Parcel Service,UPS)的方法,NCEP的多重规则法和根据雾内各物理过程间的平衡进行诊断的方法。UPS法根据低层大气稳定指数,多重规则法则根据模式输出的能见度、云、相对湿度和风速来诊断雾的发生,但两者均不能判断雾的强弱。物理过程平衡法是根据Zhou-Ferrier的雾层平衡理论所提出的雾发生及稳定时湍流强度小于某临界值的必要条件以及雾层内含水量的垂直分布公式对雾含水量及能见度进行诊断。后两种方法已被试验性地用于NCEP的短期集合预报中。预报验证表明,后处理中雾的再诊断方法可以有效地提高业务模式雾的预报能力。但总体而言,雾的预报与其他常规要素的预报相比,现仍处于较低的水平。最后讨论了模式对能见度和雾预报能力低下的原因和改善的途径。

REAL-TIME FORECASTS OF TYPHOON RAPID INTENSIFICATION IN THE NORTH WESTERN PACIFIC BASIN WITH THE NCEP OPERATIONAL HWRF MODEL

This study presents the real-time performance of the United States(US) National Centers for Environmental Prediction(NCEP) operational Hurricane Weather Research and Forecast(HWRF) model in predicting rapid intensification(RI) of typhoons in the North Western Pacific(WPAC) basin in 2013. Examination of all RI cases in WPAC during 2013 shows that the HWRF model captures a consistent vortex structure at the onset of all RI as seen in previous idealized studies with HWRF. However, HWRF has issues with predicting RI when the model vortex is initialized with intensity greater than hurricane strength. Further verification of the probability of detection(POD) and the false alarm rate(FAR) of RI forecasts shows that the HWRF model outperforms all other models used by the US Navy’s Joint Typhoon Warning Center, possessing highest POD and lowest FAR in 2013. Examination of the intensity change forecasts at different forecast lead times also confirms that the HWRF model has superior performance, particularly at the 72-h lead time with the POD index ~0.91 and the FAR index ~0.33. Such unique performance of the HWRF model demonstrates its role in helping operational agencies improve their official intensity(and RI) forecasts for tropical cyclones in the WPAC basin.

Improving Multi-Model Ensemble Forecasts of Tropical Cyclone Intensity Using Bayesian Model Averaging

This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging （BMA）, aiming to improve the accuracy of tropical cyclone （TC） intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center （Pmin）＇ The multi-model ensemble comprises three operational forecast models： the Global Forecast System （GFS） of NCEP, the Hurricane Weather Research and Forecasting （HWRF） models of NCEP, and the Integrated Forecasting System （IFS） of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution （or probability density function, PDF） of emin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models var-ied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distri-bution transformation, provided more accurate forecasts than did the best of the ensemble members （HWRF）, with a 5%-7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced ＂predictive variance＂ that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the poten-tial to be applied to routine operational forecasting.

TROPICAL CYCLONE AMOS (2016) FORECASTING CHALLENGES: A MODEL'S PERSPECTIVE

The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant challenge for forecasters and this is briefl y summarized in this report.Model forecasts initially indicated that the cyclone would track south of the Samoan Islands.However,the forecasts generally changed to a direct hit over Samoa as a Category 4 storm at approximately 0000 U TC 24April based on model cycles initialized at 0000 UTC 23 April.TC Amos’central pressure dropped from 983 hPa to 957 hPa between 0000 UTC 21 April and 0000 UTC 23April.The models did not pick up on this rapid intensif ication until the intensif ication had already begun around0000 UTC 21 April.The models also struggled to capture the rapid weakening of TC Amos due to vertical wind shear that began 0000 UTC 24 April as the cyclone continued to move north of the islands.Because of the initially ominous track forecasts for TC Amos to hit land,preparations for a Category 3 or Category 4 cyclone were underway in the Samoan islands and the population prepared for the worst.After the center of the storm moved north of the islands as a weaker storm than anticipated,the residents of the Samoan Islands were both surprised and relieved that the cyclone only gave a"glancing blow"to the islands and that the impacts were not as bad as originally feared.An in-depth evaluation of this particular tropical cyclone helps to shed some light on model def iciencies and can be used to help determine future model changes.

东亚热带与副热带季风区对流降水和层云降水季节变化特征对比分析研究

利用10年TRMM卫星2A25资料,对东亚热带和副热带季风区对流降水和层云降水的季节变化特征进行了对比分析,研究了热带和副热带季风区降水性质的差异,并结合IPCC第4次报告中24个模式的20c3m模拟资料,对现有模式在东亚热带和副热带季风区关于对流降水及层云降水的模拟能力做了一个简单的评估,分析了模式中可能存在的问题.结果表明:夏季风爆发后,东亚热带与副热带季风区对流降水和层云降水都明显增加,但热带季风区对流降水所占比重明显减少,而副热带季风区对流降水所占比重明显增加,热带和副热带季风区存在明显不同;现有模式对东亚季风区对流降水百分比的模拟普遍偏高,而对层云降水的模拟偏少,这在热带季风区尤其明显;模式较好地模拟出了副热带季风区中对流降水百分比的季节变化特征,而对热带季风区对流降水百分比的季节变化没有正确描述;研究结果表明对流降水和层云降水在时间和空间上经常同时出现,具有很强的伴随性,而模式没有正确描述这种相关性,这可能是模式对层云降水百分比模拟不好的一个重要原因.